ABSTRACT
MR based methods have gained an important role for the clinical detection and diagnosis of breast cancer. Dynamic contrast-enhanced MRI of the breast has become a robust and successful method, especially for diagnosis of high-risk cases due to its higher sensitivity compared to X-ray mammography. The application of MR based imaging methods depends on various automated image processing routines. The combination of techniques for preprocessing, quantification and visualization of datasets is necessary to achieve fast and solid assessment of valuable parameters for diagnosis. In this paper, different aspects such as registration methods for the reduction of motion artifacts, segmentation issues, as well as morphologic and dynamic lesion analysis will be reviewed with a focus on breast MRI, MR spectroscopy and MR guided biopsies of the breast, their implications and technical challenges from a computer assistance point of view.
Subject(s)
Breast Neoplasms/diagnosis , Image Processing, Computer-Assisted , Magnetic Resonance Spectroscopy/methods , Female , Germany , HumansABSTRACT
Owing to the rapid development of scanner technology, thoracic computed tomography (CT) offers new possibilities but also faces enormous challenges with respect to the quality of computer-assisted diagnosis and therapy planning. In the framework of the Virtual Institute for Computer Assistance in Clinical Radiology cooperative research project, a software application was developed to assist the radiologist in the analysis of thoracic CT data for the purpose of evaluating the response to tumor therapy. The application provides follow-up support for monitoring of tumor therapy by means of volumetric quantification of tumors and temporal registration. In addition, anatomically adequate three-dimensional visualization techniques for convenient examination of large data sets are included. With close cooperation between computer scientists and radiologists, the application was tested and optimized to achieve a high degree of usability. Several clinical studies were carried out, the results of which indicated that the application improves therapy monitoring with respect to accuracy and time required.
Subject(s)
Lung Neoplasms/diagnostic imaging , Lung Neoplasms/secondary , Radiographic Image Interpretation, Computer-Assisted , Tomography, X-Ray Computed/methods , Algorithms , Humans , Lung Neoplasms/therapyABSTRACT
Owing to the rapid development of scanner technology, thoracic computed tomography (CT) offers new possibilities but also faces enormous challenges with respect to the quality of computer-assisted diagnosis and therapy planning. In the framework of the Virtual Institute for Computer Assistance in Clinical Radiology cooperative research project, a prototypical software application was developed to assist the radiologist in functional analysis of thoracic CT data. By identifying the anatomic compartments of the lungs, the software application enables assessment of established functional CT parameters for each individual lung, pulmonary lobe, and pulmonary segment. Such region-based assessment allows a more localized diagnosis of lung diseases such as emphysema and more accurate estimation of regional lung function from CT data. With close cooperation between computer scientists and radiologists, the software application was tested and optimized to achieve a high degree of usability. Several clinical studies were carried out, the results of which indicated that the software application improves quantification in diagnosis, therapy planning, and therapy monitoring with respect to accuracy and time required.